Scientists have developed SpaMosaic, an AI-driven method to integrate fragmented spatial multi-omics datasets, enabling unified molecular maps across tissues. The tool combines contrastive learning ...

A World Bank study introduces an AI-based method using graph neural networks to break down national statistics like GDP into ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

Researchers have introduced ChemGraph, an AI-powered agentic framework that automates and streamlines computational chemistry and materials science workflows. Combining graph neural networks for ...

A universal potential for all-purpose atomic simulations has been pursued for decades, but remains challenging due to limitations in model expressiveness and dataset construction. Now, writing in the ...

Fine-grained spatial data are critical for informed decision-making in domains ranging from economic planning to environmental management. However, many statistics are only available for coarse ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...